分类： 计算机科学 >> 信息安全 分类： 计算机科学 >> 计算机应用技术 提交时间： 2024-04-23
摘要： Image steganography has become a focal point of interest for researchers due to its capacity for the covert transmission of sensitive data. Traditional diffusion models often struggle with image steganography tasks involving paired data, as their core principle of gradually removing noise is not directly suited for maintaining the correspondence between carrier and secret information. To address this challenge, this paper conducts an in-depth analysis of the principles behind diffusion models and proposes a novel framework for an image steganography diffusion model. The study begins by mathematically representing the steganography tasks of paired images, introducing two optimization objectives: minimizing the secrecy leakage function and embedding distortion function. Subsequently, it identifies three key issues that need to be addressed in paired image steganography tasks and, through specific constraint mechanisms and optimization strategies, enables the diffusion model to effectively handle paired data. This enhances the quality of the generated stego-images and resolves issues such as image clarity. Finally, on public datasets like CelebA, the proposed model is compared with existing generation model-based image steganography techniques, analyzing its implementation effects and performance parameters. Experimental results indicate that, compared to current technologies, the model framework proposed in this study not only improves image quality but also achieves significant enhancements in multiple performance metrics, including the imperceptibility and anti-detection capabilities of the images. Specifically, the PSNR of its stego-images reaches 93.14dB, and the extracted images’ PSNR reaches 91.23dB, an approximate improvement of 30% over existing technologies; the attack success rate is reduced to 2.4x10-38. These experimental outcomes validate the efficacy and superiority of the method in image steganography tasks.
分类： 地球科学 >> 地理学 提交时间： 2019-06-20 合作期刊: 《干旱区科学》
摘要： Remote sensing is an effective way in monitoring desertification dynamics in arid and semi-arid regions. In this study, we used a decision tree method based on NDVI (normalized difference vegetation index), SAVI (soil adjusted vegetation index), and vegetation cover proportion to quantify and analyze the desertification in Eritrea using Landsat data of the 1970s, 1980s and 2014. The results demonstrate that the NDVI value and the annual mean precipitation declined while the temperature increased over the past 40 a. Strongly desertified land increased from 4.82×104 km2 (38.5%) in the 1970s to 8.38×104 km2 (66.9%) in 2014: approximately 85% of the land of the country was under serious desertification, which significantly occurred in arid and semi-arid lowlands of the country (eastern, northern, and western lowlands) with relatively scarce precipitation and high temperature. The non-desertified area, mostly located in the sub-humid eastern escarpment, also declined from approximately 2.1% to 0.5%. The study concludes that the desertification is a cause of serious land degradation in Eritrea and may link to climate changes, such as low and unpredictable precipitation, and prolonged drought.
分类： 医学、药学 >> 医学、药学其他学科 分类： 数学 >> 几何与拓扑 分类： 计算机科学 >> 计算机科学的集成理论 提交时间： 2018-03-31
摘要： Labeled images are one of the most important means of scientific communication and education. However, traditional markers (arrows, lines) are point markers; do not include information about how large the feature is. We designed an efficient marker system for labeling scientific images (electron or light microscopy, CT, MRI, ultrasonography, camera pictures, etc), called the “T Area Marker, (TAM)”. The basic TAM marker looks like a “T”, composed of a line segment and a small tick on one end; it defines an imagined circle that stands on the tickless end and the diameter of the circle is equal to the length of the line segment. Thus the TAM can define an exact area rather than a single point; and the imagined circle does not break the continuity of the image (unlike traditional visible circles, rectangles, etc). A TAM with N ticks (N>1) means the diameter equals to N times the length of TAM. A TAM may also have a tail and/or several tail branches to define translation of the imagined circle, thus define complicated areas. tAreaMarker.py is free software that combines the drawing and reading of TAMs, although in most cases TAMs are easily interpreted without computer assistance.
分类： 生物学 >> 生物物理学 提交时间： 2016-05-11
Wang, Shuihua
Li, Yang
Du, Sidan
Wang, Shuihua
Zhang, Yudong
Chen, Mengmeng
Wu, Jane
Chen, Mengmeng
Wu, Jane
Chen, Mengmeng
Zhang, Yudong
Han, Liangxiu
摘要： Identification and detection of dendritic spines in neuron images are of high interest in diagnosis and treatment of neurological and psychiatric disorders (e.g., Alzheimer's disease, Parkinson's diseases, and autism). In this paper, we have proposed a novel automatic approach using wavelet-based conditional symmetric analysis and regularized morphological shared-weight neural networks (RMSNN) for dendritic spine identification involving the following steps: backbone extraction, localization of dendritic spines, and classification. First, a new algorithm based on wavelet transform and conditional symmetric analysis has been developed to extract backbone and locate the dendrite boundary. Then, the RMSNN has been proposed to classify the spines into three predefined categories (mushroom, thin, and stubby). We have compared our proposed approach against the existing methods. The experimental result demonstrates that the proposed approach can accurately locate the dendrite and accurately classify the spines into three categories with the accuracy of 99.1% for "mushroom" spines, 97.6% for "stubby" spines, and 98.6% for "thin" spines.
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